In [3]:
# Reproject trapezoidal tray to rectangular (rectify)
def snap(g1, g2, threshold=1e6):
coordinates = []
for x, y in g1.coords: # for each vertex in the first line
point = Point(x, y)
p1, p2 = nearest_points(point, g2) # find the nearest point on the second line
if p1.distance(p2) <= threshold:
# it's within the snapping tolerance, use the snapped vertex
coordinates.append(p2.coords[0])
else:
# it's too far, use the original vertex
coordinates.append((x, y))
# convert coordinates back to a LineString and return
return LineString(coordinates)
img = cv2.cvtColor(cv2.imread('test2.png'), cv2.COLOR_BGR2RGB)
masks = SamAutomaticMaskGenerator(
model=sam,
points_per_side=32, # The number of points to be sampled along one side of the image
min_mask_region_area=100, # If >0, postprocessing will be applied to remove disconnected regions and holes in masks with area smaller than min_mask_region_area
).generate(img)
tray = max(masks, key=lambda x: x["area"])
# Convert binary mask to polygon
tray = shape(next(shapes(tray["segmentation"].astype(np.uint8), mask=tray["segmentation"]))[0])
plt.imshow(img)
trapezoid = snap(tray.envelope.exterior, tray)
bounds = trapezoid.envelope.exterior
gpd.GeoSeries(trapezoid).plot(ax=plt.gca(), color="red")
gpd.GeoSeries(bounds).plot(ax=plt.gca(), color="green")
plt.show()
source_corners = np.float32(trapezoid.coords[:4])
target_corners = np.float32(bounds.coords[:4])
matrix = cv2.getPerspectiveTransform(source_corners, target_corners)
print(matrix)
img = cv2.warpPerspective(img, matrix, (img.shape[1], img.shape[0]), cv2.INTER_LINEAR, borderMode=cv2.BORDER_CONSTANT, borderValue=(0,0,0))
plt.imshow(img)
✔️ 12.1 s (2023-10-04T15:17:15/2023-10-04T15:17:27)
[[ 7.56422957e-01 -1.12537290e-02 4.17070647e+01] [-1.43934636e-01 9.26897768e-01 3.00823512e+01] [-1.98664309e-04 -2.16609195e-05 1.00000000e+00]]
Out[3]:
<matplotlib.image.AxesImage at 0x7f0df1662dc0>
